similar to: MANOVA with repeated measures in R

Dear list members, I get the following error when using the glht function to perform a post hoc analysis for an ANOVA with repeated measures: require(nlme) lme_H2H_musicians = lme(H2H ~ Emotion*Material, data=musicians, random = ~1|Subject) require(multcomp) summary(glht(lme_H2H_musicians, linfct=mcp(Type = "Tukey")), test = adjusted(type = "bonferroni")) Error in

Hello everybody, problem solved, there was a typo. I wrote Type instead of Material Best ----Messaggio originale---- Da: angelo.arcadi@virgilio.it Data: 22-giu-2012 11.05 A: <r-help@r-project.org> Ogg: Error with glht function: Error in mcp2matrix(model, linfct = linfct) : Variable(s) 'Type' have been specified in 'linfct' but cannot be found in 'model'!

Dear all, how can I perform a post hoc analysis for ANOVA with repeated measures (in presence of a balanced design)? I am not able to find a good example over internet in R...is there among you someone so kind to give me an hint with a R example please? For example, the aov result of my analysis says that there is a statistical difference between stimuli (there are 7 different stimuli). ...I

Dear All, I have a problem in understanding how the interactions of 2 ways ANOVA work, because I get conflicting results from a t-test and an anova. For most of you my problem is very simple I am sure. I need an help with an example, looking at one table I am analyzing. The table is in attachment and can be imported in R by means of this command: scrd<-

Dear all, I need an help because I don´t know how to perform the analysis in the right way, as I get different beheaviors using t-test and two ways ANOVA. In what follow I post the table, my goal and the strange results I got. I kindly ask you an help because I really don´t know how to solve this problem. So the table is this: number stimulus condition response 1

Hello everyone, this is my first post here and I hope I signed up correctly and someone will take me by the hand and help me out. I am new to R and cannot figure out what to do here... ... I want to have an User Interface that requests input. I want to save this input to a variable to use it later on. I was able to do this with a modalDiaglog (

I'm relatively new to R and I'm stuck. I'm trying to construct a surface to optimize from a multivariate dataset. The dataset contains the response of a system to various stimuli. I am trying to optimize the mix of stimuli to maximize the response. To do so, I've interpolated the various datasets of type response vs. stimuli and I now have an array of functions

Dear R-list members, I need an help with the Multidimensional Scaling analysis (MDS). So far I used the cmdscale() command in R, but I did not get the perceptual map I would love to see, and I would like to know if it is possible to get it using R, and if yes how. I also had a look to the functions isoMDS() and sammoc() but with no luck. I summarize the experiment I performed, and I would ask you

Hello, I have a dilemma that I'm hoping the R gurus will be able to help resolve. For background: My data is in the form of a (dis)similarity matrix created from taking the inverse of normalized reaction times. That is, each cell of the matrix represents how long it took to distinguish two stimuli from one another-- a square matrix of 45X45 where the diagonal values are all zero (since this

I have a data frame that is the result of a cast (reshape) operation. I deleted the variable column and tried to melt the resulting data frame. Depending on which method I use to delete the column I get different error messages when melting: > head(tinfos) vpn group trial_no item relation trial_type rt variable # 1 102 2 1 4351 diag1 distractor 8471 fix_d 27

Dear all, I have carried out a pairwise comparison study that I want to analyze using the BradleyTerry package to establish a rank order of my stimuli. However, BT does not handle ties between stimuli, so I need to find those in my data before I can use that model. The code below goes from the format of my result file(s) to a data frame suitable for BT, but as you can see, there are some ties. I

This is a question about the use of the Cox proportional hazards model to analyze event histories. I am looking at the responses of sympathetic nervous system activity to a stimulus. The activity I observe is a burst that can only occur once per heart beat cycle (e.g., a binary count). Typically bursts occur in 60-80% of the heart cycles * sensory stimuli can modify these burst probabilities.

I am trying to extract significance levels out of a robcov+ols call. For background: I am analysing data where multiple measurements(2 per topic) were taken from individuals(36) on their emotional reaction (dependent variable) to various topics (3 topics). Because I have several emotions and a rotation to do on the topics, I'd like to have the results pumped into a nice table.

This is to announce a new package MLCM on CRAN. The package provides functions for estimating perceptual scales by maximum likelihood from data collected in a conjoint measurement experiment. Data for conjoint measurement are typically collected using a psychophysical procedure. The stimuli vary along 2 or more dimensions. The observer views pairs of stimuli and judges which stimulus of each pair

This is to announce a new package MLCM on CRAN. The package provides functions for estimating perceptual scales by maximum likelihood from data collected in a conjoint measurement experiment. Data for conjoint measurement are typically collected using a psychophysical procedure. The stimuli vary along 2 or more dimensions. The observer views pairs of stimuli and judges which stimulus of each pair

Dear all, I have tried to use R for the repeated measures experiment design in a phonetic study, and in the resulting forms I met some problems which perturb the final interpretation of the results. I will explain the experiment design first: the same 7 subjects were answering a question about 25 linguistic stimuli; the stimuli were the same utterances which were processed in 3 different ways (3

Dear List, This is my first post, and I'm a relatively new R user trying to work out a mixed effects model using lme() with random effects, and a correlation structure, and have looked over the archives, & R help on lme, corClasses, & etc extensively for clues. My programming experience is minimal (1 semester of C). My mentor, who has much more programming experience, but a comparable

Dear R Help, I have a general question - I know this is the R list, but I hope someone can help me out a little as I've always found the help here to be absolutely fantastic. I have run a psychological study where participants are given multiple stimuli and their responses to those stimuli are measured on the same numerical scale, i.e., the data is something like Participant Stimulus

Hello, I am trying to test some results I have for significance. It has been recommended that I use R and I am completely new to this. Set-up: Groups: two groups of 8 subjects (16 total) Two conditions: alert and passive Measurements: responses for three different stimuli (A, B, and C) measured in each condition Experiment: Testing the order of conditions Group one: Alert A, B

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